A critical assessment of null hypothesis significance testing in quantitative communication research

Timothy R. Levine, René Weber, Craig Hullett, Hee Sun Park, Lisa L.Massi Lindsey

Research output: Contribution to journalArticlepeer-review

70 Scopus citations

Abstract

Null hypothesis significance testing (NHST) is the most widely accepted and frequently used approach to statistical inference in quantitative communication research. NHST, however, is highly controversial, and several serious problems with the approach have been identified. This paper reviews NHST and the controversy surrounding it. Commonly recognized problems include a sensitivity to sample size, the null is usually literally false, unacceptable Type II error rates, and misunderstanding and abuse. Problems associated with the conditional nature of NHST and the failure to distinguish statistical hypotheses from substantive hypotheses are emphasized. Recommended solutions and alternatives are addressed in a companion article.

Original languageEnglish
Pages (from-to)171-187
Number of pages17
JournalHuman Communication Research
Volume34
Issue number2
DOIs
StatePublished - Apr 2008

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